Abstract:

It is a fact that the use of Artificial Intelligence tools is becoming integrated into all fields, and therefore their use in design projects should not surprise us, nor should the transformation they bring to learning processes and the working methods of university students.

In the Packaging course of the Bachelor’s Degree in Industrial Design Engineering and Product Development at the Universitat Politècnica de València, students must develop a design or redesign project for a package and its associated packaging. This requires analyzing all aspects related to the package, namely: the product to be packed, its distribution environment, the physical and communicative functions of the package, and the materials, without overlooking the environmental impact and economic calculations.

Given the significant intellectual and research effort that this analysis entails, and the increasing incorporation of AI into the academic sphere, it is not surprising that in recent years a growing (and sometimes inappropriate) use of generative AI tools has been observed in addressing different sections of the project.

The use of the various tools available to students has never been a problem; therefore, the use of AI itself is not the issue, but rather the tendency to employ it as a substitute for students’ technical reasoning. This leads to solutions that, although seemingly correct, are poorly justified, disconnected from the real requirements of the project and/or based on generic analyses. A recurring example of this can be found in the section related to the distribution environment: some students ask AI for theoretical explanations about the importance of logistics instead of defining the specific distribution conditions of their product and deriving from them the design requirements for both the package and the packaging. This is a critical difference, as designing for single-unit online sales is not the same as designing for palletized export in large volumes, and the lack of specificity affects the quality of the final proposals.

Thus, this paper analyzes a significant selection of recent projects in order to compare those in which AI is used as support for creative exploration, the development of alternatives, and idea verification (best practices) with those characterized by decontextualization, technical contradictions, or generic justifications that do not address the defined design problem (poor practices). Likewise, through this analysis, the aim is to identify recurring error patterns associated with AI use, such as misalignment between analysis and formal solution, inadequate material selection, designs incompatible with industrial processes, or packaging inconsistent with the newly proposed container.

Consequently, considering the use of AI as support for iteration rather than as a final answer, the study is carried out with the intention of ultimately proposing a set of concrete recommendations for effectively integrating AI into the teaching-learning process of packaging design projects, as it becomes necessary to establish clear initial requirements before resorting to generative tools.

Keywords:

Artificial Intelligence in Design Education, Packaging Design, Project-Based Learning, Generative AI Practices, Industrial Design Engineering.